1. Identity statement | |
Reference Type | Conference Paper (Conference Proceedings) |
Site | sibgrapi.sid.inpe.br |
Holder Code | ibi 8JMKD3MGPEW34M/46T9EHH |
Identifier | 8JMKD3MGPEW34M/3U2KG6S |
Repository | sid.inpe.br/sibgrapi/2019/09.09.23.37 |
Last Update | 2019:09.09.23.37.24 (UTC) administrator |
Metadata Repository | sid.inpe.br/sibgrapi/2019/09.09.23.37.24 |
Metadata Last Update | 2022:06.14.00.09.34 (UTC) administrator |
DOI | 10.1109/SIBGRAPI.2019.00012 |
Citation Key | SantosSebeAlme:2019:AcReCo |
Title | CV-C3D: Action Recognition on Compressed Videos with Convolutional 3D Networks |
Format | On-line |
Year | 2019 |
Access Date | 2024, Apr. 28 |
Number of Files | 1 |
Size | 8878 KiB |
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2. Context | |
Author | 1 Santos, Samuel Felipe dos 2 Sebe, Nicu 3 Almeida, Jurandy |
Affiliation | 1 Universidade Federal de São Paulo - UNIFESP, Brazil 2 University of Trento - UniTn, Italy 3 Universidade Federal de São Paulo - UNIFESP, Brazil |
Editor | Oliveira, Luciano Rebouças de Sarder, Pinaki Lage, Marcos Sadlo, Filip |
e-Mail Address | jurandy.almeida@unifesp.br |
Conference Name | Conference on Graphics, Patterns and Images, 32 (SIBGRAPI) |
Conference Location | Rio de Janeiro, RJ, Brazil |
Date | 28-31 Oct. 2019 |
Publisher | IEEE Computer Society |
Publisher City | Los Alamitos |
Book Title | Proceedings |
Tertiary Type | Full Paper |
History (UTC) | 2019-09-09 23:37:24 :: jurandy.almeida@unifesp.br -> administrator :: 2022-06-14 00:09:34 :: administrator -> jurandy.almeida@unifesp.br :: 2019 |
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3. Content and structure | |
Is the master or a copy? | is the master |
Content Stage | completed |
Transferable | 1 |
Version Type | finaldraft |
Keywords | computer vision action recognition deep learning compressed domain efficiency |
Abstract | Action recognition in videos has gained substantial attention from the computer vision community due to the wide range of possible applications. Recent works have addressed this problem with deep learning methods. The main limitation of existing approaches is their difficulty to learn temporal dynamics due to the high computational load demanded for processing huge amounts of data required to train a model. To overcome this problem, we propose a Compressed Video Convolutional 3D network (CV-C3D). It exploits information from the compressed representation of a video in order to avoid the high computational cost for fully decoding the video stream. The speed up of the computation enables our network to use 3D convolutions for capturing the temporal context efficiently. Our network has the lowest computational complexity among all the compared approaches. Results of our approach in the task of action recognition on two public benchmarks, UCF-101 and HMDB-51, were comparable to the baselines, with the advantage of running at faster inference speed. |
Arrangement 1 | urlib.net > SDLA > Fonds > SIBGRAPI 2019 > CV-C3D: Action Recognition... |
Arrangement 2 | urlib.net > SDLA > Fonds > Full Index > CV-C3D: Action Recognition... |
doc Directory Content | access |
source Directory Content | there are no files |
agreement Directory Content | |
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4. Conditions of access and use | |
data URL | http://urlib.net/ibi/8JMKD3MGPEW34M/3U2KG6S |
zipped data URL | http://urlib.net/zip/8JMKD3MGPEW34M/3U2KG6S |
Language | en |
Target File | 118paper.pdf |
User Group | jurandy.almeida@unifesp.br |
Visibility | shown |
Update Permission | not transferred |
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5. Allied materials | |
Mirror Repository | sid.inpe.br/banon/2001/03.30.15.38.24 |
Next Higher Units | 8JMKD3MGPEW34M/3UA4FNL 8JMKD3MGPEW34M/3UA4FPS 8JMKD3MGPEW34M/4742MCS |
Citing Item List | sid.inpe.br/sibgrapi/2019/10.25.18.30.33 1 |
Host Collection | sid.inpe.br/banon/2001/03.30.15.38 |
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6. Notes | |
Empty Fields | archivingpolicy archivist area callnumber contenttype copyholder copyright creatorhistory descriptionlevel dissemination edition electronicmailaddress group isbn issn label lineage mark nextedition notes numberofvolumes orcid organization pages parameterlist parentrepositories previousedition previouslowerunit progress project readergroup readpermission resumeid rightsholder schedulinginformation secondarydate secondarykey secondarymark secondarytype serieseditor session shorttitle sponsor subject tertiarymark type url volume |
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7. Description control | |
e-Mail (login) | jurandy.almeida@unifesp.br |
update | |
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